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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Muse Spark 1.3MetaRemove
  2. inklingThinkingMachinesRemove
  3. GPT-6 Astra ProOpenAIRemove
muse-spark-1.3 vs inkling vs gpt-6-astra-pro
AttributeMuse Spark 1.3muse-spark-1.3inklinginklingGPT-6 Astra Progpt-6-astra-pro
Pricing
Input$1.25 / 1M$0 / 1M$10.00 / 1M
Output$4.25 / 1M$0 / 1M$50.00 / 1M
Cache Write (5m)$1.25 / 1M$10.00 / 1M
Cache Write (1h)$1.25 / 1M$10.00 / 1M
Cache Read$1.25 / 1M$0 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M
Cache Write$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaThinkingMachinesOpenAI
Categorychatchatchat
Charge typePay As You GoFreePay As You Go
Released
Description
SummaryMuse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Inkling is a general-purpose multimodal autoregressive transformer model from Thinking Machines Lab, supporting text, image, and audio inputs with text output. It is designed for a wide range of applications, including reasoning, coding, multilingual understanding, and multimodal interaction. Optimized for agentic workflows, tool use, coding assistants, chatbots, retrieval-augmented generation (RAG), and instruction following, Inkling provides a versatile foundation for production AI systems requiring robust language and multimodal capabilities.GPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.